Introduction

The woodlands of Western Port between Nyora and Grantville were surveyed with camera trapping by the Southern Brown Bandicoot Regional Recovery Group between mid 2020 to December 2022. This report maps the observed occurrences of selected species, generally where there are sufficient observations. Interactive maps are created. Several mammal species are mapped with a selection of the bird and reptile species. The sites surveyed with a camera trap are shown. The base map can be selected (using the layers icon on the left).

Methods

The methods used in this study follow the procedures described in a paper in The Victorian Naturalist, Nicholls et al (2018) and an unpublished report Nicholls et al (2022).

Data sets

Two data tables, camera table and record table are managed with the R package camptrapR.
We use the Stations.new1 camera table. This has the attributes of the Stations plus six extra appended attributes, namely the MGA coordinates, Latitude-Longitude (GDA94 decimal degrees), and two fields that measure the difference between the manually entered coordinates and the the coordinates derived programatically from the GIS file.

The camtrapR record table is the Species R data frame.

Base Map with sf

Use the modern package sf.

Species maps

A set of maps, one for each species, is produced as a PDF maps. The maps include locality (as defined by DELWP), conservation reserves and trapping stations (black dot) and species present (red square).

There are some interactive maps (below), one each for a few selected species.

List of species

List of Species, by taxa
Taxon Species
Monotreme Short-beaked Echidna
Marsupial Agile Antechinus
Dusky Antechinus
Southern Brown Bandicoot
Long-nosed Bandicoot
Common Wombat
Koala
Mountain Brushtail Possum
Common Brushtail Possum
Sugar Glider
Common Ringtail Possum
Eastern Grey Kangaroo
Black Wallaby
Placental Bush Rat
Swamp Rat
Black Rat
deer
Red Fox
Cat
Aves Painted Button-quail
Bassian Thrush
Eastern WhipBird
Reptile Lace Monitor
Blotched Blue-tongue Lizard

Map Western Port Woodlands camera trap stations with mapview

Use the interactive map. At the top left, the plus/minus icons zoom. Just below is the layers icon, it drops down to offer different background maps. In the top right is the legend listing the layers. In the bottom left, clicking the title restores the default extent to the map.

Map Southern Brown Bandicoot with mapview

Map Lace Monitor with mapview

Map Red Fox with mapview

Map Agile Antechinus with mapview

Acknowledgements

The work was funded by the Wettenhall Environment Trust with additional contributions from South Gippsland Conservation Society and Parks Victoria West Gippsland. Skills were developed with and equipment was provided by the Western Port Biosphere Reserve Foundation and its Southern Brown Bandicoot Regional Recovery Group.

The land owner and managers provided approval to survey on their land. Individuals, S Ibbetson, E Thexton, T Herring, D Wettenhall amd others contributed in the field. Colleagues, Malcolm Legg, Terry Coates and AO (Nick) Nicholls were authors for the science programme that produced these results.

The open science community developed the management and reporting tools that make it possible to handle and understand the more than 250 000 images that are the source for these results.

References

Appelhans T, Detsch F, Reudenbach C, Woellauer S (2022). mapview: Interactive Viewing of Spatial Data in R. R package version 2.11.0, https://CRAN.R-project.org/package=mapview.

Nicholls D.G., T.D. Coates and S.A. Ibbetson 2018. Assessment of the monitoring of ground-dwelling mammals in northern Western Port, Victoria. Victorian Naturalist 135(4): 96-107.

Nicholls D G , T Coates, M Legg, A O Nicholls. (2022). Ground-dwelling mammals in Western Port Woodlands: A camera trapping survey 2020-2022. Unpublished reprot to Wettenhall Environment Trust.

Niedballa Jürgen, Rahel Sollmann, Alexandre Courtiol, Andreas Wilting (2016). camtrapR: an R package for efficient camera trap data management. Methods in Ecology and Evolution 7(12), 1457-1462.

R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/